Systems that can perform natural language parsing and deep question and answer (DeepQA) may be utilized to help querying users obtain responses to queries. DeepQA illustrates how the growing accessibility of natural language content and the integration and advancement of natural language processing, information retrieval, machine learning, knowledge representation and reasoning, and parallel computation can drive open-domain automatic question and answering technology to provide meaningful answers.
Challenges may exist, however in considering the confidence associated with a given response to a query. For example, the quality of an answer, the time required finding an answer, and the confidence associated with each answer may depend on the amount of computing resources (e.g., the number of processors) allocated for performing the analysis. Currently, challenges existing in providing a system that analyzes query response quality when allocating computing resources.